Senior Workforce AI Solutions Engineer

Salary: $121,000 - 161,000 per year Requirements:

• Experience in solution architecture, software engineering, automation, cloud engineering, application integration, or a related technology field.
• Track record of delivering business-facing technical solutions from requirements gathering through implementation.
• Hands-on experience with at least one enterprise AI platform, such as Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, or a comparable technology.
• Experience with APIs, SDKs, integrations, automation technologies, and structured or unstructured enterprise data sources.
• Working knowledge of enterprise identity, authentication, authorization, and secure integration practices.
• Ability to work with both low-code and pro-code approaches and choose an appropriate method for each request.
• Strong analytical, consulting, documentation, troubleshooting, and stakeholder communication skills.
• Ability to manage multiple requests, balance business urgency with technical risk, and see work through to completion.
• Preferred: Experience building custom agents, AI assistants, agent actions, and multi-step AI workflows.
• Preferred: Experience developing MCP servers, custom skills, plugins, connectors, or similar extensibility components.
• Preferred: Experience with Microsoft Graph, REST APIs, Azure Functions, Logic Apps, Power Automate, GitHub, Visual Studio, or Visual Studio Code.
• Preferred: Knowledge of retrieval-augmented generation, enterprise search, grounding, vector search, and knowledge-management approaches.
• Preferred: Knowledge of responsible AI, data protection, security, compliance, auditability, and AI governance.
• Preferred: Experience identifying and measuring productivity, process, service-quality, or business-value improvements.
• The ideal candidate is curious about emerging AI capabilities, applies disciplined enterprise engineering, communicates technical tradeoffs clearly, and is accountable, risk-aware, and motivated to improve how employees work.

• Lead and coordinate delivery of qualified workforce AI requests, including allocating work with a collaborating coworker, providing technical direction, resolving issues, and ensuring completion.
• Manage and prioritize the request queue, partnering with intake and triage to confirm scope, readiness, ownership, dependencies, and delivery approach.
• Work with requesters to understand business processes, desired outcomes, data needs, risks, and measures of success.
• Translate business needs into practical solutions using approved platforms and technologies; estimate effort, communicate expectations, document decisions, and track progress and outcomes.
• Provide implementation documentation, transfer knowledge, and transition completed solutions to an ongoing support model.
• Design AI-enabled workflows, agents, automations, and process improvements; select implementation approaches based on business needs, technical fit, security, maintainability, and cost.
• Build solutions using simple builder experiences, low-code platforms, and pro-code development as appropriate.
• Create reusable design patterns, templates, components, and engineering standards; assess scalability, observability, supportability, and lifecycle needs before production use.
• Build and maintain purpose-specific agents, actions, prompts, workflows, and orchestration logic; develop custom skills, MCP servers, or integrations when platform capabilities are insufficient.
• Extend AI platforms using APIs, SDKs, custom connectors, functions, and other approved methods, applying source control, testing, documentation, and release-management practices.
• Design secure connections to enterprise data sources, knowledge repositories, business applications, and external functions.
• Apply modern authentication and authorization patterns, and work with application, data, security, privacy, architecture, and identity teams to establish approved access.
• Protect enterprise data across retrieval, processing, storage, and output, following least-privilege principles.
• Maintain working knowledge of enterprise AI platforms, APIs, capabilities, limitations, licensing, and integration options; evaluate new capabilities and share lessons and reusable practices with partner teams.
• Advance measurable business value from workforce AI investments through productivity, quality, service, or process improvements, while meeting enterprise security, governance, privacy, compliance, and architecture requirements.

• AI
• Azure
• ChatGPT
• Cloud
• Copilot
• GitHub
• Support
• MCP
• REST
• Security
• Visual Studio
• AI Agents
• API
• Architect
• OAuth

More:

We are collaborating with hackajob to connect professionals with this opportunity at Verisk. As a Workforce AI Solutions Engineer in our Workforce Technology Services organization, you will partner with business stakeholders across the enterprise to design, build, test, and deploy solutions using approved workforce AI platforms, including Microsoft Copilot, Copilot Studio, Claude, and ChatGPT Enterprise. You will own a queue of business-submitted requests requiring light-to-moderate implementation effort, working alongside a collaborating coworker. A partner team handles initial intake and triage, separating simple questions, training needs, and requests requiring clarification from qualified projects that need hands-on technical delivery but not a large-scale software development engagement.

last updated 42 week of 2026